1. Technical Field
This invention relates to signal processing systems. In particular, this invention relates to multi-channel speech signal processing using adaptive beamforming.
2. Related Art
Speech signal processing systems often operate in noisy background environments. For example, a hands-free voice command or communication system in an automobile may operate in a background environment which includes significant levels of wind or road noise, passenger noise, or noise from other sources. Noisy background environments result in poor signal-to-noise ratio (SNR), masking, distortion, corruption of signals, and other detrimental effects on signals. As a result, noisy background environments reduce the intelligibility and clarity of speech signals and reduce speech recognition accuracy.
Past attempts to improve signal quality in noisy background environments relied on multi-channel systems, such as systems including microphone arrays. Multi-channel systems primarily employ a General Sidelobe Canceller (GSC) which processes the speech signal along two signal paths. The first signal path suppresses the unwanted noise. The second signal path employs a non-adaptive (i.e., fixed) beamformer that synchronizes the signal of each microphone in the array. The synchronization is based on the limiting assumption that the microphone signals differ only by their time delays. Reliance on a fixed beamformer renders such systems susceptible to potentially wide variations in energy levels at each microphone in the array and the differences in SNR among the microphone signals.
In many practical applications, the SNR of each microphone signal of an array differs from the SNR of every other microphone signal obtained from the array. Under such conditions, the fixed beamformer may actually reduce performance of the noise reduction signal processing system. In particular, microphone signals with low SNR may contribute excessive noise to the beamformed output signal. Thus, past GSC implementations did not provide a consistently reliable mechanism for reducing noise, and do not provide speech command or communication systems with a consistently noise free signal.
Therefore, a need exists for an improved noise reduction signal processing system.